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Create an Apache Hudi-based near-real-time transactional data lake using AWS DMS, Amazon Kinesis, AWS Glue streaming ETL, and data visualization using Amazon QuickSight

AWS Big Data

Data analytics on operational data at near-real time is becoming a common need. Due to the exponential growth of data volume, it has become common practice to replace read replicas with data lakes to have better scalability and performance. For more information, see Changing the default settings for your data lake.

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AWS Lake Formation 2022 year in review

AWS Big Data

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference. Starting with Amazon EMR release 6.7.0,

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Moving Enterprise Data From Anywhere to Any System Made Easy

Cloudera

This blog aims to answer two questions: What is a universal data distribution service? Why does every organization need it when using a modern data stack? Every organization on the hybrid cloud journey needs the ability to take control of their data flows from origination through all points of consumption.

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Moving Enterprise Data From Anywhere to Any System Made Easy

CIO Business Intelligence

This blog aims to answer two questions: What is a universal data distribution service? Why does every organization need it when using a modern data stack? Every organization on the hybrid cloud journey needs the ability to take control of their data flows from origination through all points of consumption.

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Extend your data mesh with Amazon Athena and federated views

AWS Big Data

Amazon Athena is a serverless, interactive analytics service built on the Trino, PrestoDB, and Apache Spark open-source frameworks. Recently, Athena added support for creating and querying views on federated data sources to bring greater flexibility and ease of use to use cases such as interactive analysis and business intelligence reporting.

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Automate the archive and purge data process for Amazon RDS for PostgreSQL using pg_partman, Amazon S3, and AWS Glue

AWS Big Data

AWS Glue integrates seamlessly with AWS services like Amazon S3, Amazon Relational Database Service (Amazon RDS), Amazon Redshift , Amazon DynamoDB , Amazon Kinesis Data Streams , and Amazon DocumentDB (with MongoDB compatibility) to offer a robust, cloud-native data integration solution.

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Introducing Amazon EMR on EKS job submission with Spark Operator and spark-submit

AWS Big Data

In the following code, replace the EKS endpoint as well as the S3 bucket then run the script: /bin/spark-submit --class ValueZones --master k8s://EKS-ENDPOINT --conf spark.kubernetes.namespace=data-team-a --conf spark.kubernetes.container.image=608033475327.dkr.ecr.us-west-1.amazonaws.com/spark/emr-6.10.0:latest amazonaws.com/spark/emr-6.10.0:latest